CIOs can separate AI hype from reality by considering these areas of risk and opportunity.
A chatbot that answers consumers’ questions and directs them to the appropriate place or person is a common example of artificial intelligence (AI), and one most people have experienced personally. But it’s just one way to apply AI technologies.
AI can predict when a key sensor in a machine needs to be replaced to avoid a manufacturing line shutdown or can be used in emergency braking systems to prevent robots from significantly damaging their own components. It can forecast when units will sell out, highlight and respond to patterns in supply chains, and even identify risk factors in investments based on a business’s loan repayment behavior and credit usage.
“ Common definitions of AI focus on automation and, as a result, often fail to make clear the opportunities available to IT and business leaders”
AI-powered applications can assist healthcare providers with diagnosis and search images for early cancer detection. The technology can find key factual law passages and pinpoint how lawyers have used them in other cases; dissect how certain judges think, write and rule; and assist in mediation. It even knows when to change character voices while reading a children’s book.
“Look at how you are using technology today during critical interactions with customers — business moments — and consider how the value of those moments could be increased,” says Whit Andrews, distinguished vice president analyst at Gartner. “Then apply AI to those points for additional business value.”
The basics of artificial intelligence
Gartner defines AI as applying advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take action.
Common definitions of AI focus on automation and, as a result, often fail to make clear the opportunities available to IT and business leaders. AI is technology that emulates human performance, typically by learning from it.
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